Report on Cyber Attacks Classification in IoT-based-Healthcare Infrastructure

Home, - Write a report on Cyber Attacks Classification

Question 1 - Review and write a summary to critically analyse and report on "Cyber Attacks Classification in IoT-based-Healthcare Infrastructure".

Answer -

The attacks related to health infrastructure can be classified into various categories. There are application layer based attacks which are performed on the applications which are deployed in the hospitals for their operations. There are various types of the cyber security attacks. Ransomware is the most trending category of the malware attack in which the data of the user encrypted in demand for the hefty ransom. The session keys in the health system are threatened by the session medjacking attack. The valid session of the staff of the hospital can be hijacked by using such attack. The denial of the service attack can prevent the users of the hospital system from getting access to the system. Conti ransomware is type of the malware which is delivered with the help of the trick bot system and this malware is having high speed which is used for the encryption of the data of the organization. Email with an excel sheet is used in this for attack.

Question 2 - Write a thorough description of the importance of descriptive and predictive data analysis in cyber security. Give relevant examples and cite your sources.

Answer -

Data is used to understand the past performance of the business and the current performance of the organization in the descriptive analytics. Organizations can use this approach in order to analyze its past performance of security as well as its existing performance. The informed decisions can be made by the organization based on the descriptive analytics of the organization. There are different techniques of the descriptive analytics which include the mean, median, mode, box plot and much other such technique.

The future risks related to cyber security of the organization and the performance of the organization is forecasted based on the predictive analytics of the data. This domain provides the insights into the things that might happen in the future. There are different techniques of the predictive analytics including the decision tree, regression, artificial neural network Gradient boost model, Baysian statistics, time series analysis and the support vector machine.

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